MIT Introduction to Deep Learning | 6.S191
Are you interested in learning about deep learning and its applications? Look no further than MIT’s Introduction to Deep Learning course, 6.S191. This course is designed for students with some background in programming and machine learning, and aims to provide a comprehensive introduction to the field of deep learning.
The course covers topics such as neural networks, convolutional neural networks, recurrent neural networks, and generative models. Students will learn about the mathematical foundations of deep learning, as well as practical skills for implementing and training deep learning models using frameworks such as TensorFlow.
Course Highlights:
- Hands-on programming assignments
- Lectures by industry experts
- Guest talks from leading researchers in the field
- Access to cutting-edge research in deep learning
Course Schedule:
| Week | Topic |
|---|---|
| 1 | Introduction to Deep Learning |
| 2 | Neural Networks |
| 3 | Convolutional Neural Networks |
| 4 | Recurrent Neural Networks |
| 5 | Generative Models |
Overall, MIT’s Introduction to Deep Learning course, 6.S191, offers a unique opportunity to learn from leading experts in the field and gain hands-on experience with state-of-the-art deep learning techniques. Whether you are a student looking to expand your knowledge or a professional seeking to enhance your skills, this course is sure to provide valuable insights into the world of deep learning.
Please can anyone tell me, i am beginner and self learning these, can i do it or its too advance???!
I'm a beginner in ml and ai fields and it's amazing to have these lectures online and free. I've a doubt: the neural network showed in 33:44 shouldn't be named 'multi' layer rather than 'single' layer neural network since it has an output layer separated of the hidden layer? Thanks!
too bad, even MIT courseware gives a false definition of AI in the slide 7:40
Can absolute beginners follow these lectures???
amazing video
The mathematics which I studied this semester is completely making sense now.
Explained so well, hopefully I will get more video to watch…. Can somebody suggest me to find best free material (video) like this video for AI, I desperately want to make my career in field of data science and AI
good Presentation agood overview about deep learning thanks sir Alexander Amini
You are a great teacher. I wish my professor explained this way. 🎉
Love your style!
Mark it, learn later
Amazing for free lectures ❤
Where can we find the labs? I cant find them on the website
Thanks!
I am in a bit of a fix, hope someone in the comments or the publishers of the series can shed some light.
I am a professional embedded software engineer. I have been fiddling with the idea to develop expertise in embedded AI and thus looking for an inroad, lets call it that. Now i know there are options like TinyML(TF lite) , edge impulse and other frameworks where maybe i could jump in.
The question is, is this a good way or is it more suggested to take up an uni/grad level curriculum like this one?
I guess something that brings me to hands on implementation at the embedded level relatively quickly will be very enticing.
28:24 This is a very basic idea of deeplearning. I should have watch these lectures before I started my computer vision courses.
WOW!!!!😍My professor is chinese and I know he knows a alot of things but after watching this teacher teachin, I understood the importance of a good presentation and most importantly, what a good presentation look like.
A big Thank you to you for this great course
Just propaganda
These lectures are goated 🔥